ProgramMaster Logo
Conference Tools for TMS Specialty Congress 2025
Login
Register as a New User
Help
Submit An Abstract
Propose A Symposium
Presenter/Author Tools
Organizer/Editor Tools
About this Abstract
Meeting TMS Specialty Congress 2025
Symposium Joint Sessions of AIM, ICME, & 3DMS
Presentation Title Smart Sustainable Packaging for Local Fruits—TRACE Your Food, KNOW Your Food, TAKE CARE of Trash
Author(s) Mudra Kapoor, Parijat Deshpande, Henil Panchal, Hitanshu Sachania, Shrikant Kapse, Shankar Kausley, Beena Rai, Riddhi Jain
On-Site Speaker (Planned) Mudra Kapoor
Abstract Scope This study proposes an innovative approach to sustainable fruit packaging to ensure optimal freshness, traceability, authenticity and responsible consumption while reducing environmental impact. We integrate smart sensors on fruit packaging that provides consumers with transparent, authentic information about the product, including harvest date, farm name, nutritional properties, and disposal methods. Using Computational Materials Engineering approach and augmented AI tools, we design packaging material with high barrier functionality, sustainability, and compostability, addressing performance and environmental impact. We achieve this by screening the material requirement from our in house library of sustainable materials. The smart sustainable packaging promotes high end consumer experience to trace their food, gain nutritional information, real time assessment of quality and responsible disposal of food waste and packaging waste. This is achieved by digital tools that scan the food information in real time as input, processes it in backend and gives requisite output using mobile application.
Proceedings Inclusion? Definite: Post-meeting proceedings

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

Architecture for Developing an Image Recognition Model Workflow for Workplace Safety Application
Automated 3D Microstructural Characterization of a Dual-Phase Steel Using the RASSI Platform
Building a Self-Driving Lab From Scratch
Customizing the NIMS RDE System for Optimal Data Management
Digital Twins for Accelerated Materials Innovation
Efficient, Coupled Process-Structure-Property Simulations of Additive Manufacturing Using the “Materialize” Framework
Enhancing AI Readiness Through Data Stewardship, Modular Ontologies, and FAIR Data Workflows
FactoryNet: A Labeled Image Dataset for the Manufacturing Environment
FIB-SEM Serial Sectioning Tomography: Towards 24-Hour Time-to-Results
Generalized Graph Foundation Models as Versatile Data-Driven Digital Twins for Complex Technological Systems
Harnessing Deep Learning Conditional Diffusion Models for Microscopy Modality Transfer of Light Optical Microscopy to Electron Backscattering Microscopy Diffraction Misorientations
Harnessing Multi-Modal Metrology Data for Predictive Modeling in Laser Powder Directed Energy Deposition
Hydro Quebec Efforts Toward ICME: Characterizing the Microscale Tensile Behavior of Hydraulic Turbine Steels With Micro-Tensile and Nano-Indentation Tests
Influence of 3D Crack Networks for High Toughness Responses in Tantalum Carbides
Innovations in 3D EBSD for Advanced Materials Characterization
Laser Assisted Machining of Niobium C103 and Optimization of Machining Parameters Using AI/ML Techniques
Manufacturing and Control of Fiber Reinforced Polymer Composites Through FMEA-Based Digital Twin
Materials Microstructure Design Integrated With Image-Based Simulation
Modelling Physical-to-Virtual Feedback Flow of Digital Twins for Induction Furnace
Modular and Interoperable Materials Data Science Ontology (MDS-Onto) for Knowledge Graphs and Semantic Reasoning
NFDI MatWerk Ontology: A Framework for FAIR Data Management in the Materials Science and Engineering
NIMS's Data-Driven Materials Research Platform: Enhancing MLOps With Literature-Based Data Integration
Ontology-Based Materials Data Management for High Temperature Alloy Oxidation Data
Pinax: A Machine Learning Platform for Data-Driven Materials Development
Practical Data Management in Computational Materials for Qualification and Certification
Smart Sustainable Packaging for Local Fruits—TRACE Your Food, KNOW Your Food, TAKE CARE of Trash
The Materials Science and Engineering Knowledge Graph: Establishing a Centralized Metadata Index for Enhanced Data Integration
Toward Sentient Manufacturing
Towards Structured Data Spaces: Prototypical Application of Semantic Technologies as a Driver for Innovation in Materials Science
Transforming Materials Science With Concepts for a Semantically Accessible Data Space
Uncertainty Quantification, Error Propagation, and Sensitivity Analysis for Synchrotron X-Ray Residual Stress Measurements
Using Novel EBSD Methods to Analyze Plastic Strain in Structural Alloys
X-Ray Diffraction Analysis Using TensorFlow and FAIR Data Pipelines
"Advanced Calibration of GTN Damage Model for Aluminum Alloy AA6111 Using Digital Image Correlation and Bayesian Inference"

Questions about ProgramMaster? Contact programming@programmaster.org